Trafficability route-finding algorithm of vehicle navigation system

Abstract

The invention relates to a trafficability route-finding algorithm of a vehicle navigation system. The trafficability route-finding algorithm is characterized in that a starting point and a finishing point of a route are respectively arranged in two road networks by a trafficability road network model so that the two road networks can be communicated with each other in a passing region range so as to ensure a specified passing region is in the route-finding process from the starting point to the finishing point; a large passing region semidiameter is set when the distance of the starting point and the finishing point is far and the large passing region semidiameter is set when the road network density is small by adopting a region semidiameter adjusting scheme so as to ensure a planned route to effectively pass through the region semidiameter and not necessarily to pass through a control point; and the route is guided to pass through the specified region by adopting virtual finishing point route-finding, setting a virtual finishing point and utilizing A* algorithm and the route is guided to be planned from the specific region to the finishing point by adopting direction changing route finding and changing route finding guide cost so as to ensure the accuracy and the reliability of the results. A route planned by the trafficability route-finding algorithm can meet user's intent to pass through the passing region, can meet cost minimum standards, and can be used for various embedded vehicle navigation systems.

Description

technical field [0001] The invention relates to an optimal path planning method, in particular to a passability pathfinding algorithm for a vehicle navigation system based on a user's intention to pass through a designated area. Background technique [0002] Optimal path planning can be carried out under various criteria such as the lowest cost, avoiding road sections, and passing through specific areas. Most of the existing path planning algorithms are based on the minimum cost (distance, time, cost, etc.) criteria for the system to find the path from the starting point to the end point, and choose a cost-optimized route for the user. However, everyone hopes to have the right to participate in the choice, and users of car navigation systems often hope to be able to choose a suitable road according to their own needs. For example, some users want to pass through a certain area, but are not sure whether to pass through a certain point. Such problems belong to the system fuz...

AI Technical Summary

Problems solved by technology

When the K value is large, the path calculation efficiency of the K shortest path algorithm will be greatly reduced, and because this method has high requirements on the hardware performance of the machine, embedded devices with weaker hardware configurations actually execute the K shortest path algorithm. there will be some difficulties

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